提问人：bvowe 提问时间：8/15/2022 最后编辑：akrunbvowe 更新时间：8/15/2022 访问量：467
按组计算唯一值
Count unique values by group
问：
DATA = data.frame("TRIMESTER" = c(1,1,1,1,1,1,1,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3),
"STUDENT" = c(1,2,3,4,5,6,7,1,2,3,5,9,10,11,3,7,10,6,12,15,17,16,21))
WANT = data.frame("TRIMESTER" = c(1,2,3),
"NEW_ENROLL" = c(7,3,5),
"TOTAL_ENROLL" = c(7,10,15))
我有“数据”，想做“想要”，它有三列，对于每个“三个月”，你计算新的“学生”的数量，然后对于“TOTAL_ENROLL”，你只计算每个三个月唯一“学生”的总数。
我的尝试只计算每个三个月的数字。
library(dplyr)
DATA %>%
group_by(TRIMESTER) %>%
count()
答：
4赞
akrun
8/15/2022
#1
我们将 'STUDENT' 中的元素进行分组，得到非 NA 元素，最后做累积和 （replaceduplicatedNATRIMESTERsumcumsum)
library(dplyr)
DATA %>%
mutate(STUDENT = replace(STUDENT, duplicated(STUDENT), NA)) %>%
group_by(TRIMESTER) %>%
summarise(NEW_ENROLL = sum(!is.na(STUDENT)), .groups= 'drop') %>%
mutate(TOTAL_ENROLL = cumsum(NEW_ENROLL))
-输出
# A tibble: 3 × 3
TRIMESTER NEW_ENROLL TOTAL_ENROLL
<dbl> <int> <int>
1 1 7 7
2 2 3 10
3 3 5 15
或者用distinct
distinct(DATA, STUDENT, .keep_all = TRUE) %>%
group_by(TRIMESTER) %>%
summarise(NEW_ENROLL = n(), .groups = 'drop') %>%
mutate(TOTAL_ENROLL = cumsum(NEW_ENROLL))
# A tibble: 3 × 3
TRIMESTER NEW_ENROLL TOTAL_ENROLL
<dbl> <int> <int>
1 1 7 7
2 2 3 10
3 3 5 15
9赞
Rui Barradas
8/15/2022
#2
这是一种方法。
suppressPackageStartupMessages(library(dplyr))
DATA <- data.frame("TRIMESTER" = c(1,1,1,1,1,1,1,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3),
"STUDENT" = c(1,2,3,4,5,6,7,1,2,3,5,9,10,11,3,7,10,6,12,15,17,16,21))
DATA %>%
mutate(NEW_ENROLL = !duplicated(STUDENT)) %>%
group_by(TRIMESTER) %>%
summarise(NEW_ENROLL = sum(NEW_ENROLL)) %>%
ungroup() %>%
mutate(TOTAL_ENROLL = cumsum(NEW_ENROLL))
#> # A tibble: 3 × 3
#> TRIMESTER NEW_ENROLL TOTAL_ENROLL
#> <dbl> <int> <int>
#> 1 1 7 7
#> 2 2 3 10
#> 3 3 5 15
创建于 2022-08-14 由 reprex 软件包 （v2.0.1）
9赞
Mohamed Desouky
8/15/2022
#3
- 对于品种，我们可以使用
Base Raggregatetransform
transform(aggregate(. ~ TRIMESTER , DATA[!duplicated(DATA$STUDENT),] , length),
TOTAL_ENROLL = cumsum(STUDENT))
- 输出
TRIMESTER STUDENT TOTAL_ENROLL
1 1 7 7
2 2 3 10
3 3 5 15
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